Session 5: Collaboration Panel
Research Directions in the interplay of
Knowledge Discovery and Interactive
Visualization

5:15 PM

Session 6: Closing Session

5:55 PM

Wrap-Up

5:55 PM

End of Workshop

7.30 PM

Dinner: Future of VAKD

Workshop Description

Visual Analytics is a relatively new multidisciplinary field that
combines various research areas including knowledge discovery, data
analysis, visualization, human-computer interaction, data management,
geo-spatial and temporal data processing and statistics. The goal of Visual
Analytics is to derive insight from massive, dynamic, ambiguous, and often
conflicting data; detect the expected and discover the unexpected; provide
timely, defensible, and understandable assessments; and communicate the
assessment effectively for action. An integration of the increasing
processing power of computers with the efficient pattern recognition
abilities and domain knowledge of human analysts is a challenging and
promising road in dealing with large amounts of complex data. It will be
also a major driving force for solutions for information overload in many
research and commercial areas.

The objective of this workshop is to bring together researchers and
practitioners that are developing and applying the state-of-the-art
in visual analytics; to provide a forum for presentation and
discussion of the newest both mature and greenhouse ideas, research
and developments in visual analytics and supporting disciplines, and
to identify the short- and long-term research directions in the
field and preferences of the potential end users.

We solicit papers that will introduce new research results, present
forward-looking positional statements, or define relevant research
challenges.

Peter Eades will give a presentation titled 'It's Hard to Draw
a Graph'. It will detail methods for graph visualization, and point to
problems that have not yet been solved.

Joseph Kielman will give a presentation titled 'Research
Directions and Collaborations in Visual Analytics'. This will give some
insight on visual analytics, based on his experience, and point out a few
open research problems and possible collaborations between the visual
analytics and data mining communities.

You are invited to work the VAST 2008-2010 challenges, and use those
datasets, to illustrate your KDD/VA research. A distinct advantage
to you in using these datasets is that we will be able to compare
and contrast approaches taken by the Visual Analytics community with
yours and examine the possibilities for synergies between the two
communities. We will provide additional guidance into the adjusted
tasks to make the challenge interesting to the KDD community.

We will present examples of the VAST 2008, 2009, and
2010 challenge solutions at the workshop, as a springboard to
follow-on discussion.

We strongly encourage (but do not strictly require) all contributors to
use at least some of the challenge tasks described below to demonstrate the
methods and concepts proposed in the contributions. This will support the
discussion by making the position papers more concrete by providing a
common problem for all, as well as serve as uniform benchmark data set for
the workshop submissions.

In addition to original contributions we will consider papers based on
recently published outstanding works, given that the original papers are
adequately cited and the status is clearly stated in the contribution.

All submitted papers will be reviewed for quality and originality by the
Program Committee. Based on this review, the papers will be accepted for
oral and/or poster presentations, or rejected. The review process will not
be double-blind (i.e., the reviewers can see your identity, you do not have
to anonymize your paper).

Papers will be selected by the program committee through a peer-review
process and they will be presented in oral and/or poster sessions in the
workshop. Selected papers will be invited to be published in a special
journal issue or proceedings after the workshop, along with the conclusions
of the workshop.

Organizers

Simeon Simoff
Professor of Information Technology, Head of School
School of Computing and Mathematics,
University of Western Sydney, NSW 1797
Australia
s.simoff [at] uws.edu.au